1. Field of the Invention
The present invention relates to an optical-character-recognition (which will be referred to as “OCR”, hereinafter) apparatus and a method for verifying the result of OCR for a specific part, and particularly relates to an OCR apparatus and an OCR result verification method that are adapted to reduce the load of verifying the result of OCR.
2. Description of the Related Art
According to known OCR apparatuses and OCR methods, as disclosed in Japanese Unexamined Patent Application Publication No. 2000-10755, for example, information about the result of OCR can be transmitted, as a sound. Therefore, a user can verify the OCR result based on the output sound.
Although the rate at which OCR apparatuses in recent years recognize a character becomes considerably high, the rate is not perfect. Therefore, the user has to verify the OCR result.
According to the above-described OCR apparatuses and OCR result verification methods, the user can verify the result of OCR processing by recognizing output sound. However, if a hardly-recognizable character or a number including 1, 7, and so forth is erroneously recognized, the user often misses the error. Further, the above-described OCR apparatuses do not determine the accuracy (matching) of OCR processing. Therefore, the user does not know how accurately the number 7 and/or 1 is recognized. Therefore, if the accuracy of OCR processing is so low that “70,000 yen” is erroneously recognized, as “10,000 yen”, the user hardly notices the error.
There have been provided OCR apparatuses that can present original data to be OCR-processed and OCR data obtained by OCR processing at the same time, so as to verify a result of the OCR processing. In that case, a user verifies the result of recognition by comparing the original data to the OCR data, where the original data and the OCR data are comparatively displayed on a display.
However, even though the user compares the original data to the OCR data, where the original data and the OCR data are comparatively displayed, the OCR recognition rate is not perfect. That is to say, the total number of erroneously recognized parts is not zero, though it is small. Therefore, the comparison requires attention when verifying whether or not there are erroneously recognized parts and puts a heavy load on the user's eyes, thus increasing the load of verification on the user.